C.Evaluate Localization Performance of each Method comes from the tags reading operations.The operations cost We repeat localization procedures for 64 times to evaluate most of the time. the performance for 4 methods respectively.During the ex X.CONCLUSION periments,all 15 reference tags are used.Fig.7(c)shows the cumulative distribution(CDF)of localization error and Fig. This paper considers how to provide accurate indoor- 7(d)shows the bounds of localization error. localization by using adaptive methods,from the experimental As shown in Fig.7(c),both APS,AGC and integrat- point of view.We conduct measurements over passive RFID ed method have much better performance than the baseline tags in the realistic settings,and propose two adaptive lo- method.Compare APS method with AGC method,nearly 40% calization methods and an integrated method after analysis of localization errors is under 20cm in APS method while of experimental observations.Our experiments show that our only about 10%of errors is under 20cm in AGC method.It localization methods can achieve 31cm in average error and 2.6 seconds in average time.We believe this work gives much means the APS method can really reduce the minimum error. However,over 95%of errors is under 70cm in AGC method insight and inspiration for accurate indoor-localization using while only over 85%of errors is under 70cm.It means the passive RFID technology. APS method still suffers from some problems such as multi- ACKNOWLEDGMENT path effect in the same as baseline method.But,the AGC This work is partially supported by the National method can use the automatic feedback fingerprints to calibrate Basic Research Program of China (973)under Grant negative impact. No.2009CB320705:the National Natural Science Foundation The same result is proved in Fig.7(d),the average value of China under Grant No.61100196,61073028,61021062, the maximum value and the minimum value of localization 91218302:the JiangSu Natural Science Foundation under errors in baseline method are much worse than the other three Grant No.BK2011559. methods.The average values of errors in APS method and AGC method are almost the same.But,the maximum error REFERENCES in APS method is much larger than AGC method and the [1]H.Choi,Y.Jung,and Y.Baek,"Two-step locating system for harsh minimum error in APS method is smaller than AGC method. marine port environments,"in Proc.of IEEE International Conference It means the large errors are really calibrated by AGC method on RFID(RFD),2011,pp.106-112. and the appropriate transmitting power decided by APS really 2] N.B.Priyantha,A.Chakraborty,and H.Balakrishnan,"The cricket location-support system,"in Proceedings of the 6th annual international improves the accuracy in the best case. conference on Mobile computing and networking.ACM,200,pp.32- By integrating APS and AGC method,the integrated 43. method improves the localization performance in total range. 31 S.Azzouzi.M.Cremer,U.Dettmar,R.Kronberger,and T.Knie,"New The average error of localization is 32.5cm and 85%of errors measurement results for the localization of uhf rfid transponders using an angle of arrival (aoa)approach,"in Proc.of IEEE International is under 50cm Conference on RFID (RFID),2011,pp.91-97. [4] R.Miesen,F.Kirsch,and M.Vossiek,"Holographic localization of pas- D.Evaluate Integrated Method with Different Number of Ref- sive uhf rfid transponders,"in Proc.of IEEE International Conference erence Tags on RFID (RFID),2011,pp.32-37. In regard to 15 deployed reference tags,we respectively [5] J.Hightower,G.Borriello,and R.Want,"Spoton:An indoor 3d location sensing technology based on rf signal strength,"Univ.Washington use all of them,10 of them,5 of them to estimate the Tech.Rep.,2000. position of target tag by integrated method.Fig.7(e)shows the [6] J.Brchan,L.Zhao,J.Wu,R.Williams,and L.Perez,"A real-time rfid average value and bounds of error in 64 localization procedure. localization experiment using propagation models,"in Proc.of /EEE We note that the average error is small by more number of International Conference on RFID (RFID).2012,pp.141-148. reference tags.The minimum error is almost the same because 17] Z.Yang.C.Wu,and Y.Liu,"Locating in fingerprint space:Wireless the method works well in some small areas within entire indoor localization with little human intervention."in Proc.of /EEE MobiCOM.2012. localization area.In those areas,estimated positions are both accurate no matter how many reference tags are deployed [8] A.Rai,K.K.Chintalapudi,V.N.Padmanabhan,and R.Sen,"Zee: Zero-effort crowdsourcing for indoor localization,"in Proc.of ACM However,we note that the maximum error by 10 reference MOBICOM.2012. tags is smaller than it by 15 reference tags.It is because more 9叨 T.Deyle,H.Nguyen,M.Reynolds,and C.Kemp,"Rf vision:Rfid interference existed by more reference tags.But the influence receive signal strength indicator (rssi)images for sensor fusion and of more reference tags is tiny compared with average error. mobile manipulation,"in Proc.of IEEE/RSJ International Conference The maximum error by 5 reference tags is much larger than on Intelligent Robots and Systems,2009,pp.5553-5560. others caused by lacking of reference tags. [10]L.Ni,Y.Liu,Y.Lau,and P.Abhishek,"Landmarc:Indoor location sensing using active rfid,"Wireless Nerworks,vol.10,no.6,pp.701- 710.2004. E.Evaluate Time Delay of each Method [11]Y.Zhao.Y.Liu.and L.M.Ni."Vire:Active rfid-based localization We respectively measure time delays of 4 methods with using virtual reference elimination,"in Proc.of the International 64 localization procedures.The average time delay of baseline Conference on Parallel Processing,2007. method and AGC method are both about 2.1 seconds.It means [12] W.Zhu,J.Cao,Y.Xu,L.Yang,and J.Kong,"Fault-tolerant rfid reader localization based on passive rfid tags,"in Proc.of IEEE INFOCOM, the time-consumption of grid-based calibration procedure is 2012,pp.2183-2191. very small.The APS method and Integrated method cost about [13] L.Yang,J.Cao,W.Zhu,and S.Tang,"A hybrid method for achieving 0.45 seconds more than the other two methods.It is caused by high accuracy and efficiency in object tracking using passive rfid."in the procedure of finding the appropriate transmitting power. Proc.of IEEE International Conference on Pervasive Computing and During the experiments,we note that most time-consumption Communications (PerCom),2012,pp.109-115.C. Evaluate Localization Performance of each Method We repeat localization procedures for 64 times to evaluate the performance for 4 methods respectively. During the ex￾periments, all 15 reference tags are used. Fig. 7(c) shows the cumulative distribution (CDF) of localization error and Fig. 7(d) shows the bounds of localization error. As shown in Fig. 7(c), both APS, AGC and integrat￾ed method have much better performance than the baseline method. Compare APS method with AGC method, nearly 40% of localization errors is under 20cm in APS method while only about 10% of errors is under 20cm in AGC method. It means the APS method can really reduce the minimum error. However, over 95% of errors is under 70cm in AGC method while only over 85% of errors is under 70cm. It means the APS method still suffers from some problems such as multi￾path effect in the same as baseline method. But, the AGC method can use the automatic feedback fingerprints to calibrate negative impact. The same result is proved in Fig. 7(d), the average value , the maximum value and the minimum value of localization errors in baseline method are much worse than the other three methods. The average values of errors in APS method and AGC method are almost the same. But, the maximum error in APS method is much larger than AGC method and the minimum error in APS method is smaller than AGC method. It means the large errors are really calibrated by AGC method and the appropriate transmitting power decided by APS really improves the accuracy in the best case. By integrating APS and AGC method, the integrated method improves the localization performance in total range. The average error of localization is 32.5cm and 85% of errors is under 50cm. D. Evaluate Integrated Method with Different Number of Ref￾erence Tags In regard to 15 deployed reference tags, we respectively use all of them, 10 of them, 5 of them to estimate the position of target tag by integrated method. Fig. 7(e) shows the average value and bounds of error in 64 localization procedure. We note that the average error is small by more number of reference tags. The minimum error is almost the same because the method works well in some small areas within entire localization area. In those areas, estimated positions are both accurate no matter how many reference tags are deployed. However, we note that the maximum error by 10 reference tags is smaller than it by 15 reference tags. It is because more interference existed by more reference tags. But the influence of more reference tags is tiny compared with average error. The maximum error by 5 reference tags is much larger than others caused by lacking of reference tags. E. Evaluate Time Delay of each Method We respectively measure time delays of 4 methods with 64 localization procedures. The average time delay of baseline method and AGC method are both about 2.1 seconds. It means the time-consumption of grid-based calibration procedure is very small. The APS method and Integrated method cost about 0.45 seconds more than the other two methods. It is caused by the procedure of finding the appropriate transmitting power. During the experiments, we note that most time-consumption comes from the tags reading operations. The operations cost most of the time. X. CONCLUSION This paper considers how to provide accurate indoor￾localization by using adaptive methods, from the experimental point of view. We conduct measurements over passive RFID tags in the realistic settings, and propose two adaptive lo￾calization methods and an integrated method after analysis of experimental observations. Our experiments show that our localization methods can achieve 31cm in average error and 2.6 seconds in average time. We believe this work gives much insight and inspiration for accurate indoor-localization using passive RFID technology. ACKNOWLEDGMENT This work is partially supported by the National Basic Research Program of China (973) under Grant No.2009CB320705; the National Natural Science Foundation of China under Grant No. 61100196, 61073028, 61021062, 91218302; the JiangSu Natural Science Foundation under Grant No. BK2011559. REFERENCES [1] H. Choi, Y. Jung, and Y. Baek, “Two-step locating system for harsh marine port environments,” in Proc. of IEEE International Conference on RFID (RFID), 2011, pp. 106–112. [2] N. B. Priyantha, A. Chakraborty, and H. Balakrishnan, “The cricket location-support system,” in Proceedings of the 6th annual international conference on Mobile computing and networking. ACM, 2000, pp. 32– 43. [3] S. Azzouzi, M. Cremer, U. Dettmar, R. Kronberger, and T. Knie, “New measurement results for the localization of uhf rfid transponders using an angle of arrival (aoa) approach,” in Proc. of IEEE International Conference on RFID (RFID), 2011, pp. 91–97. [4] R. Miesen, F. Kirsch, and M. Vossiek, “Holographic localization of pas￾sive uhf rfid transponders,” in Proc. of IEEE International Conference on RFID (RFID), 2011, pp. 32–37. [5] J. Hightower, G. Borriello, and R. Want, “Spoton: An indoor 3d location sensing technology based on rf signal strength,” Univ. Washington, Tech. Rep., 2000. [6] J. Brchan, L. Zhao, J. Wu, R. Williams, and L. Perez, “A real-time rfid localization experiment using propagation models,” in Proc. of IEEE International Conference on RFID (RFID), 2012, pp. 141–148. [7] Z. Yang, C. Wu, and Y. Liu, “Locating in fingerprint space: Wireless indoor localization with little human intervention,” in Proc. of IEEE MobiCOM, 2012. [8] A. Rai, K. K. Chintalapudi, V. N. Padmanabhan, and R. Sen, “Zee: Zero-effort crowdsourcing for indoor localization,” in Proc. of ACM MOBICOM, 2012. [9] T. Deyle, H. Nguyen, M. Reynolds, and C. Kemp, “Rf vision: Rfid receive signal strength indicator (rssi) images for sensor fusion and mobile manipulation,” in Proc. of IEEE/RSJ International Conference on Intelligent Robots and Systems, 2009, pp. 5553–5560. [10] L. Ni, Y. Liu, Y. Lau, and P. Abhishek, “Landmarc: Indoor location sensing using active rfid,” Wireless Networks, vol. 10, no. 6, pp. 701– 710, 2004. [11] Y. Zhao, Y. Liu, and L. M. Ni, “Vire: Active rfid-based localization using virtual reference elimination,” in Proc. of the International Conference on Parallel Processing, 2007. [12] W. Zhu, J. Cao, Y. Xu, L. Yang, and J. Kong, “Fault-tolerant rfid reader localization based on passive rfid tags,” in Proc. of IEEE INFOCOM, 2012, pp. 2183–2191. [13] L. Yang, J. Cao, W. Zhu, and S. Tang, “A hybrid method for achieving high accuracy and efficiency in object tracking using passive rfid,” in Proc. of IEEE International Conference on Pervasive Computing and Communications (PerCom), 2012, pp. 109–115